Abstract: In recent years, optical remote sensing image salient object detection (ORSI-SOD) has made substantial progress. Nevertheless, it remains an open-ended research area with complex challenges.

We ventured into dangerous waters for some underwater metal detecting, but what we didn’t expect was to be surrounded by crocodiles and a massive python. This video takes you into the wild, where we ...

Abstract: Small object detection in remote sensing images remains challenging due to limited feature resolution and complex backgrounds. Conventional detectors, due to fixed receptive fields and ...

Abstract: Adverse weather conditions significantly impact the performance of autonomous driving object detection systems, leading to reduced detection accuracy and an increased false detection rate.

Abstract: The loss function and feature extraction framework are essential parts of the algorithm design and significantly affect the accuracy of oriented object detection in remote sensing images.

Abstract: Fine-grained object detection (FOD) is essential in many remote sensing image interpretation tasks. Existing FOD methods have achieved remarkable progress in modeling discriminative features ...

Abstract: With the emergence of various large-scale deep-learning models, in remote sensing images, the object detection effect is also plagued by complex calculations, high costs, and high ...

Abstract: Object detection in aerial imagery, particularly from unmanned aerial vehicles (UAVs) and remote sensing platforms, is crucial but faces significant challenges such as modality misalignment, ...

Abstract: The perception of night scenes is of crucial importance for driving safety. In the dimly lit night environment, as the visibility of objects decreases, both experienced and inexperienced ...

Abstract: Detecting small objects and managing occlusions remain persistent challenges in object detection tasks, particularly in complex scenarios with diverse environments or densely packed scenes.